This dataset represents trip destinations on a different geographic
level than the origins stored in the object cents_sf
.
Examples
destinations_sf
#> Simple feature collection with 87 features and 6 fields
#> Geometry type: POINT
#> Dimension: XY
#> Bounding box: xmin: -1.571298 ymin: 53.79647 xmax: -1.492713 ymax: 53.83734
#> Geodetic CRS: WGS 84
#> First 10 features:
#> WZ11CD LAD11CD COWZEW_SG COWZEW_SGN COWZEW_G
#> 524 E33012352 E08000035 3 Metro suburbs 3d
#> 1936 E33010351 E08000035 2 Top jobs 2c
#> 2006 E33012331 E08000035 5 Manufacturing and distribution 5b
#> 2712 E33012280 E08000035 3 Metro suburbs 3a
#> 2730 E33010390 E08000035 7 Servants of society 7c
#> 2799 E33012310 E08000035 3 Metro suburbs 3d
#> 2996 E33012370 E08000035 3 Metro suburbs 3a
#> 3133 E33009663 E08000035 2 Top jobs 2b
#> 8057 E33013885 E08000035 3 Metro suburbs 3d
#> 8648 E33012279 E08000035 3 Metro suburbs 3b
#> COWZEW_GN geometry
#> 524 Suburban metro infrastructure POINT (-1.492713 53.81042)
#> 1936 Big city life POINT (-1.53781 53.80131)
#> 2006 Industrial units POINT (-1.533468 53.80576)
#> 2712 Metro surburban distribution POINT (-1.540438 53.81724)
#> 2730 Major hospitals POINT (-1.540901 53.80167)
#> 2799 Suburban metro infrastructure POINT (-1.521311 53.81683)
#> 2996 Metro surburban distribution POINT (-1.530386 53.80194)
#> 3133 Adminstrative centres POINT (-1.532527 53.80963)
#> 8057 Suburban metro infrastructure POINT (-1.56543 53.81388)
#> 8648 Cosmopolitan metro suburban mix POINT (-1.555112 53.82408)